Stochastic Dual Dynamic Programming in Julia
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Updated
Jun 4, 2024 - Julia
Stochastic Dual Dynamic Programming in Julia
An intuitive modeling interface for infinite-dimensional optimization problems.
Data-driven decision making under uncertainty using matrices
Coordinate and Incremental Aggregated Optimization Algorithms
Julia implementation of stochastic optimization algorithms for large-scale optimal transport.
From SMPS to solved in one step: implementation of Angulo, Ahmed and Dey (2016) Improved Integer L-Shaped Method
A Stochastic Primal-Dual Proximal Splitting Method for Risk-Averse Optimal Control of PDEs
Slime Mold swarm optimization - efficient derivative free biologically inspired solver
Prototyping of matrix free Newton methods in Julia
A flexible framework for SD-like algorithms in Julia.
Maximum Weight Two Stage Spanning Tree
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